Combining the advantages of distributed optimization and machine learning, distributed learning frameworks are needed to enable wireless devices to collaboratively build a shared learning model with training taken place locally. One of the most promising distributed learning algorithms is the
emerging federated learning (FL) [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]}, [11]}, [12]}, [13]}, [14]}, [15]} framework is anticipated in future Internet of Things
(IoT) systems.
In FL, wireless devices can cooperatively execute a learning task by
only uploading local learning models to the base station (BS) instead of sharing the entirety of
their training data, as illustrated in Fig. REF  [16]}.
Since the data center cannot access the local data sets at the users, FL can protect data privacy of the users.
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